View the online visualization here.
Design Statement
The Data:
The data I collected for my personal data project was on my sleeping habits throughout the semester from about half way through September – November. I recorded the time I went to bed and the time I woke up everyday, allowing me to calculate the total hours I slept every night. I also recorded things like the location of my sleeping, whether or not I slept alone and reasoning if my hours seemed abnormal. This allowed me to collect consistent data throughout the semester where I could search for trends and skews within the data that are able to answer some questions about my sleeping habits.
The data varied from night to night depending on certain factors like whether or not I stayed or late to study or stayed out late, along with things like waking up early to do complete homework or make a drive back to pullman from the west-side. I was able to collect the data through a google sheet which I updated every day with how many hours I slept, where I slept and any reasoning I had for it. This worked fairly effectively, however there would be days I’d forget to record my data and then have to think back a day or two and might have lost some of the accuracy.
The Visualizations:
I found that when creating my static graphs, bar graphs tended to work the best. My data is discrete and not continuous over time thus it made sense to use the individualized sections that a bar graph allows for. In these bar graphs I could measure things like the hours I accumulated every day, where I was accumulating those hours and what that looked like throughout an average week.
With my interactive graphics I chose to specifically look at where I was sleeping and the different ways to represent that information. I used a couple different bubble charts to really allow for a visualization of how much I was sleeping some places versus others. I then got very detailed wit it to show day by day, allowing for a complete circle of where I was sleeping.
In order to keep things looking the same I used different shades of orange within my designs, to keep a straight forward design. I think it was able to be presented in a simplistic ways, which was one of my original goals.
While creating my visualization I came to understand that my data correlating around where I slept and which day of the week it was was the most interesting. I was able to find a few correlations that I wasn’t expecting and learn a thing or two about my sleeping habits as a whole.
Insights:
One of the largest insights I was able to learn from my data was my sleeping habits during the weekdays compared to the weekends. Originally I had always thought I lost the most about of sleep on the weekend because I typically stay out late and don’t get to bed till the early hours of the morning. However, after analyzing my data through a few different charts I was able to see that yes, I was in fact losing sleep on the weekend, but I was losing more during a couple weekdays, Monday and Tuesday in particular. After thinking about why this reasoning was I realized it was because of my habits procrastinating and waiting to turn in a majority of my school assignments before their due dates on Mondays and Tuesdays.
I think if I were to collect a large scale of data like this again I would look into using an app that gives me reminders to collect the data so I don’t forget at times. I would also approach the collection with a specific question in mind, so that way when I begin to collect different aspects, I will know what I plan to use.
I wasn’t necessarily left with any unanswered questions, but rather a better understanding of what exactly my sleeping schedule looks like. I think going into this project I had a lot of unjustified assumptions about the way I slept. However now I feel comfortable to say I understand my habits and have learned a few things I might like to change.